1. Introduction
The Riemann zeta-function
,
, is defined, for
, by
where the infinite product is taken over all prime numbers, and has analytic continuation over the whole complex plane, except for the point
which is a simple pole with residue 1. The function
and its value distribution play an important role not only in analytic number theory but in mathematics in general.
It is well known by a Bohr and Courant work [
1] that the set of values of
with any fixed
is dense in
. Voronin obtained [
2] the infinite-dimensional version of the Bohr–Courant theorem, proving the so-called universality of
. This means that every non-vanishing analytic function in the strip
can be approximated by shifts
. We recall the modern version of the Voronin theorem. Denote by
the class of compact subsets of the strip
D with connected complements, and by
with
the class of continuous non-vanishing functions on
K that are analytic in the interior of
K. Then, for
,
and every
, the inequality
is true; see, for example, [
3,
4,
5,
6]. Thus, we have that there are infinitely many shifts
approximating a given function
.
The above theorem is of continuous type because
in shifts
can take arbitrary real values. If
runs over a certain discrete set, then we have the discrete universality that was proposed in [
7]. Denote by
the cardinality of a set
A, and suppose that
N runs over the set of non-negative integers. If
K and
are as above, then we have, for
and
,
Approximations of analytic functions by more general discrete shifts were considered in [
8,
9,
10].
Denote by
the positive imaginary parts of non-trivial zeros
of the function
. Discrete universality theorems with shifts
were obtained in [
11,
12]. In [
11], for this the Riemann hypothesis was used, while in [
12], the weak form of the Montgomery pair correlation conjecture [
13] was involved. More precisely, the estimate, for
,
was required. Analogical results for more general functions were given in [
14,
15].
On the other hand, all above theorems are non-effective in the sense that any concrete shift approximating a given analytic function is not known. This shortcoming leads to the idea of universality in intervals as short as possible containing
with approximating property. The first result in this direction was obtained in [
16].
Theorem 1. Suppose that , and . Then, for every , The aim of this paper is the universality of the function
in short intervals with shifts
. In this case, the estimate (1) is not sufficient. Therefore, for
with
, we use the following hypothesis:
which, as estimate (1), also gives a certain information on the pair correlation of non-trivial zeros, differently from estimate (1), however, in short intervals.
Theorem 2. Suppose that , and estimate (2) are true. Let and . Then, for every and , Moreover, “lim inf” can be replaced by “lim” for all but at most countably many .
Theorem 2 has a generalization for certain compositions
. Denote by
the space of analytic functions on the strip
D endowed with the topology of uniform convergence on compacta. Moreover, let
and, for the operator
and distinct complex numbers
,
Then we have
Theorem 3. Suppose that estimate (2) is true, , and is a continuous operator such that . For , let and be a continuous function on K, and analytic in the interior of K. For , let K be an arbitrary compact subset of D, and . Then, for every and , Moreover “lim inf” can be replaced by “lim” for all but at most countably many .
For example, the operators and satisfy the hypotheses of Theorem 3 with and .
The proofs of Theorems 2 and 3 use probabilistic limit theorems for measures in the space
. Denote by
the Borel
-field of the space
. The main limit theorem will be proved for
as
. We divide its proof into four sections.
2. A Limit Theorem on the Torus
Denote by
the unit circle on the complex plane, by
the set of all prime numbers, and define the set
where
for all
. With the product topology and pointwise multiplication, the torus
is a compact topological Abelian group. Therefore, on
, the probability Haar measure
can be defined, and we have the probability space
. Denote by
the
pth component of an element
,
.
In this section, we will prove a limit theorem for
as
.
Before the statement of a limit theorem for as , we will recall some useful results that will be used in its proof. Denote by the number of non-trivial zeros of in the region .
Lemma 1 (von Mongoldt formula)
. For the proof, see, for example, [
17].
Denote by the number of zeros of with and .
Lemma 2. Suppose that with . Then, for , uniformly in σ, Proof of the lemma can be found in [
18].
For positive , denote by the von Mongoldt function if , and zero, otherwise.
Lemma 3. For positive and , with every .
Proof. The lemma is Theorem 2 of [
19] with
. □
Lemma 4. Suppose that with . Then, for positive , as , Proof. Since
in view of Lemma 3,
An application of Lemma 1 gives
and
This together with Equation (3) proves the lemma. □
Now, we state the limit theorem for .
Theorem 4. Suppose that, for any , . Then converges weakly to the Haar measure as .
Proof. Denote by
,
, the Fourier transform of
, i.e.,
where the star “*” means that only a finite number of integers
are distinct from zero. Thus, by the definition of
,
Now, suppose that
. Since the set
is linearly independent within the field of rational numbers
, in that case we have
Thus, we will estimate the sum
It is easily seen that
where
in
, and
in
. Obviously,
Therefore, by Lemma 2 and estimate (2),
This, and estimates (7) and (8) show that
Lemma 4 with
implies
Therefore, in view of estimate (9),
This together with Equation (6) shows that
and the lemma is proved because the right-hand side of the latter equality is the Fourier transform of the measure
. □
3. A Limit Theorem for Absolutely Convergent Series
Let
be a fixed number, and
for
. Extend the function
to the set
by setting
and define
and
Then the latter series are absolutely convergent for
[
5]. Consider the function
defined by
The absolute convergence of the series implies the continuity of .
For
, define
Theorem 5. Suppose that . Then converges weakly to the measure .
Proof. The theorem follows from the equality
continuity of the function
, Theorem 4 and Theorem 5.1 of [
20]. □
The weak convergence of
is closely connected to that of
as
. Define
Then
is an
-valued random element on the probability space
[
5]. We recall that the latter infinite product, for almost all
, is uniformly convergent on compact subsets
. Denote by
the distribution of the random element
, i.e.,
The following statement is very important.
Proposition 1. The probability measure converges weakly to measure as .
Proof. For
, define
It is known that
, as
, converges weakly to
[
5]. Moreover,
, as
, and
, as
, converge weakly to the same probability measure on
. Thus,
converges weakly to
as
. □
7. Proof of Universality
Theorems 2 and 3 are derived from Theorem 6 and Corollary 1, respectively, by using the Mergelyan theorem on the approximation of analytic functions by polynomials [
23].
Proof of Theorem2. It is well known, see, for example, [
5], that the support of the measure
is the set
S. Define the set
where
is a polynomial. Obviously,
. Therefore,
is an open neighbourhood of an element of the support of the measure
. Thus, by a property of the support,
This, Theorem 6 and the equivalent of weak convergence in terms of open sets show that
Hence, by the definition of
and
,
Now, we apply the Mergelyan theorem and choose the polynomial
satisfying
This and inequality (22) prove the first part of the theorem.
To prove the second part of the theorem, define the set
Then the set
is a continuity set of the measure
for all but at most countably many
. This remark, Theorem 6 and the equivalent of weak convergence of probability measures in terms of open sets show that
for all but at most countably many
. Inequality (23) implies the inclusion
. Therefore, in view of inequality (21), we have
. This, Equation (24) and the definitions of
and
prove the second part of the theorem. □
Proof of Theorem 3. Denote by
the support of the measure
. We observe that
contains the closure of the set
. Actually, let
and
G be any open neighborhood of
g. Then the set
is open as well, and lies in
S. Hence,
because
S is the support of
. Therefore,
This shows that contains the set and its closure.
Case . By the Mergelyan theorem, there exists a polynomial
such that
Then,
for all
if
is small enough. Therefore, by the Mergelyan theorem again, we find a polynomial
such that
Since
, the set
is an open subset of
. Hence,
This inequality together with Corollary 1, inequalities (25) and (26) prove the theorem in the case of the lower density.
In the case of density, consider the set
defined in the proof of Theorem 2 which is a continuity set of the measure
for all but at most countably many
. Therefore, by Corollary 1,
Inequalities (25) and (26) show that . Thus, by inequality (27), . This, Equation (28) and the definitions of and prove the theorem in the case of density.
Case . In this case, the function lies in . Therefore, the Mergelyan theorem is not needed, and the theorem follows immediately from Corollary 1. □